The use of deep learning (DL) for the analysis and diagnosis of biomedical and health care
problems has received unprecedented attention in the last decade. The technique has …

The recent advances in embedded processing have enabled the vision based systems to
detect fire during surveillance using convolutional neural networks (CNNs). However, such …

Fire disasters are man-made disasters, which cause ecological, social, and economic
damage. To minimize these losses, early detection of fire and an autonomous response are …

This cutting-edge volume, Computer Vision and Recognition Systems: Research
Innovations and Trends, focuses on how artificial intelligence can be used to give computers …

The detection of manmade disasters particularly fire is valuable because it causes many
damages in terms of human lives. Research on fire detection using wireless sensor network …

Blind or visually impaired people face special difficulties in daily life. With the advances in
vision sensors and computer vision, the design of wearable vision assistance system is …

Since fire is one of the most serious types of accidents that can occur, there is always a need
for improvement in fire detection capabilities. Convolutional neural networks (CNNs) have …

Image content analysis plays a dynamic role in various computer vision applications. These
contents can be either visual (ie color, shape, texture) or the textual (ie text appearing within …

Of late, China has made significant strides in wastewater management. However, there is
substantial variation in wastewater management across different regions in China. This …

Night-time pedestrian retrieval is a cross-modality retrieval task of retrieving person images
between day-time visible images and night-time thermal images. It is a very challenging …